Cerebral blood flow regulation and cognitive performance in hypertension
Bibliographic record
Abstract
We examined the relation between transcranial Doppler (TCD) markers of cerebral blood flow regulation and cognitive performance in hypertension (HT) patients to evaluate the predictive value of these markers for cognitive decline. We assessed dynamic cerebral autoregulation (dCA), vasoreactivity to carbon dioxide, and neurovascular coupling (NVC) in the middle (MCA) and posterior (PCA) cerebral arteries of 52 patients. Neuropsychological evaluation included the Montreal Cognitive Assessment and tests covering attention, executive function, processing speed, and memory. Notably, reduced rate time in the PCA significantly predicted better processing speed ( p = 0.003). Furthermore, reduced overshoot systolic cerebral blood velocity in the PCA and reduced phase in the VLF range in the MCA ( p = 0.021 and p = 0.017, respectively) significantly predicted better memory. Intriguingly, enhanced dCA in the MCA predicted poorer memory performance, while reduced NVC in the PCA predicted both superior processing speed and memory performance. These findings suggest that HT-induced changes in cerebral hemodynamics impact cognitive performance. Further research should verify these observations and elucidate whether these changes represent adaptive responses or neurovascular inefficiency. TCD markers might provide insights into HT-related cognitive decline.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".